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F1-mikro×Skor-F1×
BidangEvaluasi ModelEvaluasi Model
KeluargaMCDMMCDM
Tahun asal2000s1979
PencetusMulti-class evaluation communityC. J. van Rijsbergen
TipeEvaluation metricEvaluation metric
Sumber perintisPowers, D. M. (2011). Evaluation: From Precision, Recall and F-Measure to ROC, Informedness, Markedness and Correlation. Journal of Machine Learning Technologies, 2(1), 37-63. link ↗van Rijsbergen, C. J. (1979). Information Retrieval (2nd ed.). Butterworth-Heinemann. link ↗
AliasMicro F1, Frequency-weighted average F1F-measure, Harmonic Mean
Terkait45
RingkasanMicro-averaged F1 computes the F1-score by aggregating true positives, false positives, and false negatives across all classes, then calculating a single metric. It is equivalent to accuracy in multi-class classification and is useful when class distributions reflect their natural importance.The F1-score is the harmonic mean of precision and recall, providing a single metric that balances both concerns. It was introduced by van Rijsbergen in information retrieval and has become a standard metric for evaluating classification models where both precision and recall are important.
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ScholarGateBandingkan metode: Micro-averaged F1 · F1-Score. Diakses 2026-06-18 dari https://scholargate.app/id/compare